Reflecting on 2025
Last year, I kept my reflection private. This year, I'm writing publicly, partly for accountability, partly to document my thinking. If there's one thing 2025 taught me, it's that you learn by building, not by consuming content that masquerades as education.
I've been reading a lot this year: Nassim Taleb on embracing uncertainty rather than predicting it, Andrej Karpathy on understanding systems by building them from scratch, Scott Alexander on probabilistic thinking and epistemic humility. They've shaped how I approach problems.
On learning by doing
STAT 305 was the hardest course I took this year. Bayesian statistics felt abstract until I started implementing it in OCaml for the Jane Street Advent of FPGA competition. There's something about encoding probability distributions in a functional language that forces real understanding. You can't handwave through code. Writing functions that manipulate uncertainty made the theory click in a way lectures never did.
This connects to something Karpathy emphasizes: real learning isn't frictionless. It should feel like mental sweating. The "Learn X in 10 minutes" videos are entertainment, not education. Deep understanding comes from allocating real time blocks, taking notes, rebuilding concepts in your own words, and most importantly, building actual things.
On uncertainty and antifragility
Taleb's ideas about antifragility resonated with me this year. Some things benefit from volatility and randomness. The barbell strategy (playing it safe in some areas while taking asymmetric bets in others) maps well to how I'm thinking about 2026. Stable academic performance, experimental side projects. Low-risk foundation, high-upside exploration.
More fundamentally, I'm learning to make peace with uncertainty rather than trying to predict outcomes. I can't know how things will turn out with research applications, internship searches, or projects. But I can position myself to gain from unexpected opportunities and avoid catastrophic downside.
On probabilistic thinking
Scott Alexander writes about epistemic learned helplessness: the recognition that on most topics outside your expertise, confident arguments can be equally convincing whether they're right or wrong. The solution isn't to become paralyzed, but to think probabilistically. Assign rough confidence levels. Update based on evidence. Recognize when you're reasoning versus rationalizing.
I'm trying to apply this to how I evaluate opportunities and make decisions. Not "is this the perfect choice" but "what's the expected value given uncertainty." Not "am I sure this will work" but "what would change my confidence level."
What actually mattered
The moments I'll remember aren't the accomplishments. They're studying with friends until the library closed. Orientation week chaos. Poker nights. The people I met through research, hackathons, open source work.
I'm grateful for everyone I've connected with this year and everyone I've grown alongside. I'm equally grateful for the people I've drifted from. Sometimes letting go is as important as holding on.
Looking ahead to 2026
Every six months I barely recognize who I was half a year ago. So I'm cautious about predictions. But here's what I'm thinking about:
- Just build things. Stop overthinking outputs. Build for the sake of learning and exploring possibilities. The act of doing matters more than the result.
- Keep solving problems. Lately I've been doing LeetCode out of genuine enjoyment rather than interview prep grind. I hope that continues.
- Learn deeply. Right now I'm interested in probability, uncertainty, and how Bayesian thinking applies to decision-making under incomplete information.
- Improve time management. I had more free time this year than I realized but often slipped into low-priority tasks instead of meaningful work.
- Participate in hackathons. Build more, ship more.
- Meet new people.